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YINGYING ZHU Assistant Professor Computer Science, University of Texas at Arlington Arlington TX Email: yingying dot zhu at uta dot edu |
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I am working in the Computer Science and Engineering Department, University of Texas at Arlington as an assistant professor and also a guest researcher working in clinical center, NIH.
I was a Staff Scientist working with
Ronald M. Summers
at Clinical Center, National Institutes of Health.
I work on the intersection of computer vision, medical image analysis, bioinformatics and machine learning with the goal of developing machine learning tools for solving real-world problems.
I am currently looking for PhD student to working on
machine learning, computer vision and medical data analysis.
Details can be found here. contact: yingying.zhu@uta.edu
I did a postdoc at Cornell University working with Mert Sabuncu and postdoc in UNC Chapel Hill working with Guorong Wu. I obtained my Ph.D. from University of Queensland, Australia under the supervision of Simon Lucey (currently research associate professor in CMU, Pittsburgh, USA). |
News
Aug. 2023, we released a new large scale medical imaging difference VQA dataset and published the paper in KDD 2023!
Project Page
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Jan. 2022, Served as Reviewer of MICCAI 2022!
Dec. 2021, One paper accepted by Medical Image Analysis!
Oct. 2021 One paper accepted by BMVC 2021!
Oct. 2021, One paper accepted by EMNLP 2021!
Sep. 2021, Served as Senior PC member of AAAI 2022!
July, 2021, We are organizing CVPR 2021 Tutorial on Medical Imaging Analysis!
Select Publications
Medical-Diff-VQA: A Large-Scale Medical Dataset for Difference Visual Question Answering on Chest X-Ray Images
Xinyue Hu , Lin Gu , Qiyuan An , Mengliang Zhang , liangchen liu , Kazuma Kobayashi , Tatsuya Harada , Ronald Summers , Yingying Zhu KDD 2023
People taking photos that faces never share: Privacy Protection and Fairness Enhancement from Camera to User Junjie Zhu,Lin Gu,Xiaoxiao Wu,Zheng Li,Tatsuya Harada ,Yingying Zhu AAAI 2023
MetaTeacher: Coordinating Multi-Model Domain Adaptation for Medical Image Classification Zhenbin Wang, Mao Ye, Xiatian Zhu, Liuhan Peng, Liang Tian, Yingying Zhu Advances in Neural Information Processing Systems 2022
Exploring Resolution and Degradation Clues as
Self-supervised Signal for Low Quality Object
Detection Ziteng Cui, Yingying Zhu, Lin Gu, Guo-Jun, Xiaoxiao Li,
Renrui Zhang
, Zenghui Zhang
, and Tatsuya Harada ECCV 2022
Global-Local Attention Network with Multi-task Uncertainty Loss for Abnormal Lymph Node Detection in MR Images Shuai Wang, Yingying Zhu, Sungwon Lee, Daniel C Elton, Thomas C Shen, Youbao Tang, Yifan Peng, Zhiyong Lu, Ronald M Summers Medical Image Analysis 2022
Leveraging Human Selective Attention for Medical Image Analysis with Limited Training Data
Yifei Huan
,XiaoxiaoLi， linjin Yang, Lin Gu，Yingying Zhu, Hirofumi Seo, Qiuming Meng，Tatsuya Harada, Yoichi Sato BMVC，2021
Automated Generation of Accurate \& Fluent Medical X-ray Reports
Hoang T.N. Nguyen, Dong Nie, Taivanbat Badamdorj, Yujie Liu, Yingying Zhu, Jason Truong, Li Cheng
EMNLP，2021
Learning Structure from Visual Semantic Features and Radiology Ontology for Lymph Node Classification on MRI
Yingying Zhu, ShuaiWang, Qingyu Chen, Sungyong Lee, Thomas Shen, Daniel Elton, Zhiyong Lu, Ronald Summers
International Workshop on Machine Learning in Medical Imaging 2021
Source data‐free domain adaptation of object detector through domain‐specific perturbation
Lin Xiong, Mao Ye, Dan Zhang, Yan Gan, Xue Li, Yingying Zhu International Journal of Intelligent Systems，2021
Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen:
Toward automated and accessible classification of age-related macular degeneration
Qingyu Chen , Tiarnan D L Keenan , Alexis Allot , Yifan Peng , Elvira Agrón , Amitha Domalpally , Caroline C W Klaver ,
Daniel T Luttikhuizen , Marcus H Colyer , Catherine A Cukras , Henry E Wiley , M Teresa Magone , Chantal Cousineau-Krieger , Wai T Wong ,
Yingying Zhu , Emily Y Chew, Zhiyong Lu , AREDS2 Deep Learning Research Group J Am Med Inform Assoc， 2021
COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature Yifan Peng, Yuxing Tang, Sungwon Lee, Yingying Zhu, Ronald M. Summers, Zhiyong Lu to appear in IEEE Transaction on Big Data 2020
Automatic recognition of abdominal lymph nodes from clinical text Yifan Peng, Sungwon Lee, Shuai Wang, Qingyu Chen, Yingying Zhu, Ronald M. Summers, Zhiyong Lu clinical NLP 2020
Atherosclerotic Plaque Burden on Abdominal CT:
Automated Assessment with Deep Learning on Noncontrast and Contrast-enhanced Scans Ronald M. Summers, Daniel C. Elton, Sungwon Lee,
Yingying Zhu, Jiamin Liu , Mohammedhadi Bagheri, Veit Sandfort,
Peter C. Grayson , Nehal N. Mehta,
Peter A. Pinto, W. Marston Linehan,
Alberto A. Perez , Peter M. Graffy , Stacy D. O’Connor, Perry J. Pickhardt Academic Radiology, 2020
An Interpretable Generative Model for Abnormal Disease Separation and Radiorealistic Normal ChestX-ray Synthesis Youbao Tang, Yuxing Tang, Yingying Zhu, Jing Xiao, Ronald M. Summers to appear in Medical Image Analysis 2020
Cross-Domain Medical Imaging Translation using Shared Gaussian Mixture Model Yingying Zhu, Youbao Tang, Yuxing Tang, Daniel C. Elton, Sungwon Lee, Perry J. Pickhardt, Ronald M. Summers MICCAI 2020
E2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans Youbao Tang, Yuxing Tang, Yingying Zhu, Ronald M. Summers Early Accepted by MICCAI 2020
Image Translation by Latent Union of Subspaces for Cross-Domain Plaque Segmentations Yingying Zhu, Daniel C. Elton, Sungwon Lee, Perry J. Pickhardt, Ronald M. Summers Medical Imaging with Deep Learning (MIDL) 2020
Long Range Early Diagnosis of Alzheimer's Disease Using Longitudinal MR Imaging Data Yingying Zhu, Minjeong Kim, Xiaofeng Zhu, Guorong Wu to appear in Medical Image Analysis 2020
Detecting Cannabis-Associated Cognitive Impairment Using Resting-State fNIRS
Yingying Zhu, Jodi Gilman, Anne Eden Evins, Mert Sabuncu MICCAI 2019, oral presentation, accept rate<5%
A Bayesian Disease Progression Model for Clinical Trajectories
Yingying Zhu, Mert Sabuncu GRAIL 2018, Beyond MIC 2018, oral presentation
Dynamic fMRI networks predict success in a behavioral weight loss program among older adults
Fatemeh Mokhtari, W Jack Rejeski, Yingying Zhu, Guorong Wu, Sean L Simpson, Jonathan H Burdette, Paul J Laurienti Neuroimage 2018
Dynamic Hyper-Graph Inference Framework for Computer-Assisted Diagnosis of Neurodegenerative Diseases
Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Jin Yan, Daniel Kaufer, Guorong Wu IEEE transactions on medical imaging 38 (2), 608-616, 2018
A Probabilistic Disease Progression Model for Predicting Future Clinical Outcome
Yingying Zhu, Mert R Sabuncu arXiv preprint arXiv:1803.05011 2018
Personalized diagnosis for Alzheimer's disease
Yingying Zhu, Minjeong Kim, Xiaofeng Zhu, Jin Yan, Daniel Kaufer and Guorong Wu MICCAI 2017
Multi-modal classification of neurodegenerative disease by progressive graph-based transductive learning
Zhengxia Wang, Xiaofeng Zhu, Ehsan Adeli, Yingying Zhu, Feiping Nie, Brent Munsell, Guorong Wu Medical Image Analysis 2017
A tensor statistical model for quantifying dynamic functional connectivity
Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Jin Yan, Guorong Wu IPMI 2017
A novel dynamic hyper-graph inference framework for computer assisted diagnosis of neuro-diseases Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Jin Yan, Guorong Wu IPMI 2017
Progressive graph-based transductive learning for multi-modal classification of brain disorder disease
Zhengxia Wang, Xiaofeng Zhu, Ehsan Adeli, Yingying Zhu, Chen Zu, Feiping Nie, Dinggang Shen, Guorong Wu MICCAI 2016
Reveal consistent spatial-temporal patterns from dynamic functional connectivity for autism spectrum disorder identification
Yingying Zhu, Xiaofeng Zhu, Han Zhang, Wei Gao, Dinggang Shen, Guorong Wu MICCAI 2016
Early diagnosis of Alzheimer's disease by joint feature selection and classification on temporally structured support vector machine
Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Dinggang Shen, Guorong Wu MICCAI 2016, oral presentation, accept rate < 5%
Complex non-rigid motion 3d reconstruction by union of subspaces
Yingying Zhu, Dong Huang, Fernando De La Torre, Simon Lucey CVPR 2014
Convolutional sparse coding for trajectory reconstruction
Yingying Zhu, Simon Lucey IEEE transactions on pattern analysis and machine intelligence 2014
Teaching CSE 5368 Neural Networks Fall 2020 CSE 6363 Machine Learning Spring 2022 and Fall 2021 |
